代码

Dashboard Panel for displaying information on the chart MetaTrader 5

这段代码展示了如何创建一个仪表盘,在图表上显示所有相关信息

Trade Classes in Python - CTade, CSymbol, CPositionInfo, etc. MetaTrader 5

MetaTrader 5 Python 中类似于 MQL5 的 Python 交易类

文章

Python-MetaTrader 5 Strategy Tester (Part 01): Trade Simulator MetaTrader 5

The MetaTrader 5 module offered in Python provides a convenient way of opening trades in the MetaTrader 5 app using Python, but it has a huge problem, it doesn't have the strategy tester capability present in the MetaTrader 5 app, In this article series, we will build a framework for back testing

Implementing Practical Modules from Other Languages in MQL5 (Part 03): Schedule Module from Python, the OnTimer Event on Steroids MetaTrader 5

The schedule module in Python offers a simple way to schedule repeated tasks. While MQL5 lacks a built-in equivalent, in this article we’ll implement a similar library to make it easier to set up timed events in MetaTrader 5

Data Science and ML (Part 46): Stock Markets Forecasting Using N-BEATS in Python MetaTrader 5

N-BEATS is a revolutionary deep learning model designed for time series forecasting. It was released to surpass classical models for time series forecasting such as ARIMA, PROPHET, VAR, etc. In this article, we are going to discuss this model and use it in predicting the stock market

Implementing Practical Modules from Other Languages in MQL5 (Part 02): Building the REQUESTS Library, Inspired by Python MetaTrader 5

In this article, we implement a module similar to requests offered in Python to make it easier to send and receive web requests in MetaTrader 5 using MQL5

Implementing Practical Modules from Other Languages in MQL5 (Part 01): Building the SQLite3 Library, Inspired by Python MetaTrader 5

The sqlite3 module in Python offers a straightforward approach for working with SQLite databases, it is fast and convenient. In this article, we are going to build a similar module on top of built-in MQL5 functions for working with databases to make it easier to work with SQLite3 databases in MQL5

Data Science and ML (Part 45): Forex Time series forecasting using PROPHET by Facebook Model MetaTrader 5

The Prophet model, developed by Facebook, is a robust time series forecasting tool designed to capture trends, seasonality, and holiday effects with minimal manual tuning. It has been widely adopted for demand forecasting and business planning. In this article, we explore the effectiveness of

Sending Messages from MQL5 to Discord, Creating a Discord-MetaTrader 5 Bot MetaTrader 5

Similar to Telegram, Discord is capable of receiving information and messages in JSON format using it's communication API's, In this article, we are going to explore how you can use discord API's to send trading signals and updates from MetaTrader 5 to your Discord trading community

Data Science and ML (Part 44): Forex OHLC Time series Forecasting using Vector Autoregression (VAR) MetaTrader 5

Explore how Vector Autoregression (VAR) models can forecast Forex OHLC (Open, High, Low, and Close) time series data. This article covers VAR implementation, model training, and real-time forecasting in MetaTrader 5, helping traders analyze interdependent currency movements and improve their trading

Data Science and ML (Part 43): Hidden Patterns Detection in Indicators Data Using Latent Gaussian Mixture Models (LGMM) MetaTrader 5

Have you ever looked at the chart and felt that strange sensation… that there’s a pattern hidden just beneath the surface? A secret code that might reveal where prices are headed if only you could crack it? Meet LGMM, the Market’s Hidden Pattern Detector. A machine learning model that helps identify

Data Science and ML (Part 42): Forex Time series Forecasting using ARIMA in Python, Everything you need to Know MetaTrader 5

ARIMA, short for Auto Regressive Integrated Moving Average, is a powerful traditional time series forecasting model. With the ability to detect spikes and fluctuations in a time series data, this model can make accurate predictions on the next values. In this article, we are going to understand what